Bibliographic record
Abstract
INTRODUCTION Preventive percutaneous coronary intervention (PCI) refers to the treatment of high-risk plaque before the occurrence of any adverse events. Typically, the decision to perform preventive treatment is made when the expected event rate of the underlying condition outweighs the potential short- and long-term complications of the procedure. This approach is also applicable to the treatment of coronary disease. In recent years, advances in understanding atherosclerotic plaque progression and identifying high-risk plaques, along with technological progress in coronary devices, have shifted the balance between the risks of the underlying condition and those of percutaneous treatment. THE CONCEPT OF VULNERABLE PLAQUE The understanding of high-risk coronary plaques, also known as vulnerable plaques, has evolved over the years. Initially, a vulnerable plaque was often considered an angiographically nonsignificant stenosis that was prone to rupture and cause acute coronary syndrome.1 The PROSPECT study was the first landmark trial to focus on the natural history of vulnerable plaques, assessed using intravascular ultrasound with virtual histology.2 This trial was the first to define specific criteria for plaque vulnerability, notably thin-cap fibroatheroma (TCFA). TCFA is characterized by a lipid-rich plaque with a necrotic core, separated from the vessel lumen by a thin fibrotic cap. The trial also identified 2...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.052 | 0.014 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".